166 lines
9.8 KiB
Markdown
166 lines
9.8 KiB
Markdown
# Room list sorting
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It's so complicated it needs its own README.
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![](img/RoomListStore2.png)
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Legend:
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* Orange = External event.
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* Purple = Deterministic flow.
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* Green = Algorithm definition.
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* Red = Exit condition/point.
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* Blue = Process definition.
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## Algorithms involved
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There's two main kinds of algorithms involved in the room list store: list ordering and tag sorting.
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Throughout the code an intentional decision has been made to call them the List Algorithm and Sorting
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Algorithm respectively. The list algorithm determines the primary ordering of a given tag whereas the
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tag sorting defines how rooms within that tag get sorted, at the discretion of the list ordering.
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Behaviour of the overall room list (sticky rooms, etc) are determined by the generically-named Algorithm
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class. Here is where much of the coordination from the room list store is done to figure out which list
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algorithm to call, instead of having all the logic in the room list store itself.
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Tag sorting is effectively the comparator supplied to the list algorithm. This gives the list algorithm
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the power to decide when and how to apply the tag sorting, if at all. For example, the importance algorithm,
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later described in this document, heavily uses the list ordering behaviour to break the tag into categories.
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Each category then gets sorted by the appropriate tag sorting algorithm.
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### Tag sorting algorithm: Alphabetical
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When used, rooms in a given tag will be sorted alphabetically, where the alphabet's order is a problem
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for the browser. All we do is a simple string comparison and expect the browser to return something
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useful.
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### Tag sorting algorithm: Manual
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Manual sorting makes use of the `order` property present on all tags for a room, per the
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[Matrix specification](https://matrix.org/docs/spec/client_server/r0.6.0#room-tagging). Smaller values
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of `order` cause rooms to appear closer to the top of the list.
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### Tag sorting algorithm: Recent
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Rooms get ordered by the timestamp of the most recent useful message. Usefulness is yet another algorithm
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in the room list system which determines whether an event type is capable of bubbling up in the room list.
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Normally events like room messages, stickers, and room security changes will be considered useful enough
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to cause a shift in time.
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Note that this is reliant on the event timestamps of the most recent message. Because Matrix is eventually
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consistent this means that from time to time a room might plummet or skyrocket across the tag due to the
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timestamp contained within the event (generated server-side by the sender's server).
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### List ordering algorithm: Natural
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This is the easiest of the algorithms to understand because it does essentially nothing. It imposes no
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behavioural changes over the tag sorting algorithm and is by far the simplest way to order a room list.
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Historically, it's been the only option in Element and extremely common in most chat applications due to
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its relative deterministic behaviour.
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### List ordering algorithm: Importance
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On the other end of the spectrum, this is the most complicated algorithm which exists. There's major
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behavioural changes, and the tag sorting algorithm gets selectively applied depending on circumstances.
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Each tag which is not manually ordered gets split into 4 sections or "categories". Manually ordered tags
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simply get the manual sorting algorithm applied to them with no further involvement from the importance
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algorithm. There are 4 categories: Red, Grey, Bold, and Idle. Each has their own definition based off
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relative (perceived) importance to the user:
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* **Red**: The room has unread mentions waiting for the user.
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* **Grey**: The room has unread notifications waiting for the user. Notifications are simply unread
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messages which cause a push notification or badge count. Typically, this is the default as rooms get
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set to 'All Messages'.
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* **Bold**: The room has unread messages waiting for the user. Essentially this is a grey room without
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a badge/notification count (or 'Mentions Only'/'Muted').
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* **Idle**: No useful (see definition of useful above) activity has occurred in the room since the user
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last read it.
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Conveniently, each tag gets ordered by those categories as presented: red rooms appear above grey, grey
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above bold, etc.
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Once the algorithm has determined which rooms belong in which categories, the tag sorting algorithm
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gets applied to each category in a sub-list fashion. This should result in the red rooms (for example)
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being sorted alphabetically amongst each other as well as the grey rooms sorted amongst each other, but
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collectively the tag will be sorted into categories with red being at the top.
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## Sticky rooms
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When the user visits a room, that room becomes 'sticky' in the list, regardless of ordering algorithm.
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From a code perspective, the underlying algorithm is not aware of a sticky room and instead the base class
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manages which room is sticky. This is to ensure that all algorithms handle it the same.
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The sticky flag is simply to say it will not move higher or lower down the list while it is active. For
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example, if using the importance algorithm, the room would naturally become idle once viewed and thus
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would normally fly down the list out of sight. The sticky room concept instead holds it in place, never
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letting it fly down until the user moves to another room.
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Only one room can be sticky at a time. Room updates around the sticky room will still hold the sticky
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room in place. The best example of this is the importance algorithm: if the user has 3 red rooms and
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selects the middle room, they will see exactly one room above their selection at all times. If they
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receive another notification which causes the room to move into the topmost position, the room that was
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above the sticky room will move underneath to allow for the new room to take the top slot, maintaining
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the sticky room's position.
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Though only applicable to the importance algorithm, the sticky room is not aware of category boundaries
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and thus the user can see a shift in what kinds of rooms move around their selection. An example would
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be the user having 4 red rooms, the user selecting the third room (leaving 2 above it), and then having
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the rooms above it read on another device. This would result in 1 red room and 1 other kind of room
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above the sticky room as it will try to maintain 2 rooms above the sticky room.
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An exception for the sticky room placement is when there's suddenly not enough rooms to maintain the placement
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exactly. This typically happens if the user selects a room and leaves enough rooms where it cannot maintain
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the N required rooms above the sticky room. In this case, the sticky room will simply decrease N as needed.
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The N value will never increase while selection remains unchanged: adding a bunch of rooms after having
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put the sticky room in a position where it's had to decrease N will not increase N.
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## Responsibilities of the store
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The store is responsible for the ordering, upkeep, and tracking of all rooms. The room list component simply gets
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an object containing the tags it needs to worry about and the rooms within. The room list component will
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decide which tags need rendering (as it commonly filters out empty tags in most cases), and will deal with
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all kinds of filtering.
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## Filtering
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Filters are provided to the store as condition classes and have two major kinds: Prefilters and Runtime.
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Prefilters flush out rooms which shouldn't appear to the algorithm implementations. Typically this is
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due to some higher order room list filtering (such as spaces or tags) deliberately exposing a subset of
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rooms to the user. The algorithm implementations will not see a room being prefiltered out.
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Runtime filters are used for more dynamic filtering, such as the user filtering by room name. These
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filters are passed along to the algorithm implementations where those implementations decide how and
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when to apply the filter. In practice, the base `Algorithm` class ends up doing the heavy lifting for
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optimization reasons.
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The results of runtime filters get cached to avoid needlessly iterating over potentially thousands of
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rooms, as the old room list store does. When a filter condition changes, it emits an update which (in this
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case) the `Algorithm` class will pick up and act accordingly. Typically, this also means filtering a
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minor subset where possible to avoid over-iterating rooms.
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All filter conditions are considered "stable" by the consumers, meaning that the consumer does not
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expect a change in the condition unless the condition says it has changed. This is intentional to
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maintain the caching behaviour described above.
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One might ask why we don't just use prefilter conditions for everything, and the answer is one of slight
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subtlety: in the cases of prefilters we are knowingly exposing the user to a workspace-style UX where
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room notifications are self-contained within that workspace. Runtime filters tend to not want to affect
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visible notification counts (as it doesn't want the room header to suddenly be confusing to the user as
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they type), and occasionally UX like "found 2/12 rooms" is desirable. If prefiltering were used instead,
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the notification counts would vary while the user was typing and "found 2/12" UX would not be possible.
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## Class breakdowns
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The `RoomListStore` is the major coordinator of various algorithm implementations, which take care
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of the various `ListAlgorithm` and `SortingAlgorithm` options. The `Algorithm` class is responsible
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for figuring out which tags get which rooms, as Matrix specifies them as a reverse map: tags get
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defined on rooms and are not defined as a collection of rooms (unlike how they are presented to the
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user). Various list-specific utilities are also included, though they are expected to move somewhere
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more general when needed. For example, the `membership` utilities could easily be moved elsewhere
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as needed.
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The various bits throughout the room list store should also have jsdoc of some kind to help describe
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what they do and how they work.
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